网络与信息安全学报2024，Vol.10Issue(5)：175-187,13.DOI:10.11959/j.issn.2096-109x.2024076
基于垂直分割的个人数据隐私保护方法
Personal data privacy protection method based on vertical partitioning
摘要
Abstract
In distributed environments,vertical partitioning had been an effective method to protect user privacy.However,current vertical partitioning strategies assumed that there was no collusion among the CSPs(Cloud Ser-vice Providers)involved in data storage.This study explored how to protect user data privacy when collusion might exist between CSP.Assuming n CSP participated in data storage,with no more than k of these potentially colluding,this paper defined a(k,n)-security for vertical partitioning and introduced an automated computation scheme for vertical partitioning based on machine learning—the MLVP scheme.This MLVP scheme utilized machine learning algorithms to analyze the correlation between attributes,optimized all correlations,and transformed the vertical par-titioning problem into a satisfiability problem,which was then solved using a satisfiability solver.Moreover,the se-curity of the MLVP scheme was theoretically analyzed.To validate the effectiveness of the MLVP scheme,experi-ments were conducted on real datasets to compare the impact of different machine learning algorithms and levels of privacy protection on the effectiveness and performance of the vertical partitioning.The experiments also compared the MLVP scheme with two other schemes that did not consider collusion among CSP,Oriol's and Ciriani's schemes,in terms of computation and query speeds.The results showed that the MLVP scheme was slightly slower in computation speed to ensure security against partial CSP collusion.However,it improved the query speed by 32.6%and 8.8%compared to the aforementioned schemes,respectively.关键词
垂直分割/隐私保护/k-匿名模型/机器学习/可满足性问题Key words
vertical partitioning/privacy protection/k-anonymity/machine learning/satisfiability problem分类
信息技术与安全科学引用本文复制引用
阮华锋,李睿,罗凯伦..基于垂直分割的个人数据隐私保护方法[J].网络与信息安全学报,2024,10(5):175-187,13.基金项目
国家重点研发计划(2021YFB3101303) （2021YFB3101303）
国家自然科学基金(61972089,62206055) The National Key R&D Project of China(2021YFB3101303),The National Natural Science Foundation of China(61972089,62206055) （61972089,62206055）
